Title

Authors

Pawan Sharma^{1, 2}, Komal Saxena², Sanjay Mishra¹ & Ajay Kumar²*

Affiliation

¹School of Biotechnology, IFTM University, Lodhipur Rajput, Delhi Road (NH-24), Moradabad, 244001, U.P., India; ²Institute of Biomedical Education and Research, Mangalayatan University, Aligarh, 202145, India

Email

ajaymtech@gmail.com; *Corresponding author

Article Type

Hypothesis

Date

Received April 14, 2014; Revised May 13, 2014; Accepted May 26, 2014; Published June 30, 2014

Japanese encephalitis (JE), a viral disease has significantly increased worldwide especially, in the developing region due to challenges in immunization, vector control and lack of appropriate treatment methods. An effective, yet an expensive heat-killed vaccine is available for the disease. Therefore, the design and development of short peptide vaccine candidate is promising. We used immune-informatics methods to perform a comprehensive analysis of the entire JEV proteome of north Indian isolate to identify the conserved peptides binding known specific HLA alleles among the documented JEV genotypes 1, 2, 3, 4 and 5. The prediction analysis identified 102 class I (using propred I) and 118 class II (using propred) binding peptides at 4% threshold value. These predicted HLA allele binding peptides were further analyzed for potential conserved region using IEDB (an immune epitope database and analysis resource). This analysis shows that 78.81% of class II (in genotype 2) and 76.47% of HLA I (in genotype 3) bound peptides are conserved. The peptides IPIVSVASL, KGAQRLAAL, LAVFLICVL and FRTLFGGMS, VFLICVLTV, are top ranking with potential super antigenic property by binding to all HLA allele members of B7 and DR4 super-types, respectively. This data finds application in the design and development of short peptide vaccine candidates and diagnostic agents for JE following adequate validation and verification. 

Keywords

Immunoinformatics, epitope, short peptide, supertype, vaccine.

Citation

Sharma et al.   Bioinformation 10(6): 334-341 (2014)
 

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.